Meet the Data Rescuers: 3

Kyle Miller works on staff at Carnegie Mellon University, and was working in the Checking and Bagging team on the Outdoor Air Quality dataset from the Environmental Protection Agency. While he was waiting for the large datasets to download and upload (“most of our group’s work is waiting for data to process”), Kyle expressed that he was hopeful that this work would lead to new connections and collaboration, because the agencies that collect these data don’t always talk to each other. Creating this repository of data, he said, could have a significant social and scientific benefit. Current mood: optimistic.

Vishal Dugar. Photo by Lauren B. Collister, licensed CC-BY.

Vishal Dugar was working on the Seeder and Sorter group and is a graduate student in Robotics at Carnegie Mellon University. He participates in a student group called “Tech for Society” that investigates technology for social good. His group had processed 250 links by the middle of the event, and he said that the “sheer scale of the datasets is the most surprising thing that I’ve seen this afternoon.”

Vishal said that 90% of the datasets that he investigated were easy to process, but 10% needed more work to archive. He was impressed by the good organization of the datasets he was looking at and, while he doesn’t typically use government datasets in his work, he hoped that his work would lead to increased use for citizen science and research projects. “It’s nice to use my skills to do something good for people.” Current mood: exhilarated.

Sarah Riccitelli. Photo by Lauren B. Collister, licensed CC-BY.

Sarah Riccitelli is a student at the University of Pittsburgh pursuing a Masters in Library and Information Science and heard about the Data Rescue event from her professor, Nora Mattern, who is an organizer of the event. She studies archives and is working on a research project about the perception of archives and how events like Data Rescue impact that image. She participated in the Researcher Track, investigating what data were able to be automatically processed and which needed more attention.

Current mood: Hopeful. She was worried that nobody would attend the event, but was happy to see the great turnout and hoped that this would lead to improved connections between data scientists in the area.